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Long-Term In Vivo Imaging of Multiple Organs at the Single Cell Level

Overview of attention for article published in PLOS ONE, January 2013
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Title
Long-Term In Vivo Imaging of Multiple Organs at the Single Cell Level
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0052087
Pubmed ID
Authors

Benny J. Chen, Yiqun Jiao, Ping Zhang, Albert Y. Sun, Geoffrey S. Pitt, Divino Deoliveira, Nicholas Drago, Tong Ye, Chen Liu, Nelson J. Chao

Abstract

Two-photon microscopy has enabled the study of individual cell behavior in live animals. Many organs and tissues cannot be studied, especially longitudinally, because they are located too deep, behind bony structures or too close to the lung and heart. Here we report a novel mouse model that allows long-term single cell imaging of many organs. A wide variety of live tissues were successfully engrafted in the pinna of the mouse ear. Many of these engrafted tissues maintained the normal tissue histology. Using the heart and thymus as models, we further demonstrated that the engrafted tissues functioned as would be expected. Combining two-photon microscopy with fluorescent tracers, we successfully visualized the engrafted tissues at the single cell level in live mice over several months. Four dimensional (three-dimensional (3D) plus time) information of individual cells was obtained from this imaging. This model makes long-term high resolution 4D imaging of multiple organs possible.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 5%
France 1 5%
Unknown 19 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 29%
Student > Ph. D. Student 3 14%
Professor 2 10%
Other 1 5%
Student > Master 1 5%
Other 3 14%
Unknown 5 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 19%
Medicine and Dentistry 3 14%
Agricultural and Biological Sciences 2 10%
Immunology and Microbiology 2 10%
Engineering 2 10%
Other 2 10%
Unknown 6 29%